Patent GB-1017841-A (GB)
Title: Learning machine
Inventor: LESTI ARNOLD
IPC: G06V30/194
Filed: 1962-08-06
Abstract: 1,017,841. Automatic learning circuits. ANDROMEDA Inc. Feb. 6, 1962, No. 4610/62. Heading G4R. In a learning circuit, i.e. a circuit which will produce a predetermined response to each of a series of input signal patterns, the input patterns are applied each as an ordered group of n separate values and is interacted in the circuit with a stored memory function (also containing an ordered group of n separate values) the circuit serving to form products of corresponding applied and stored values which are summed to develop a classifying signal. This signal has one of a number of predetermined values which is converted by a register unit to a standing output identifying the input pattern. The input signal patterns may be a series of instantaneous sample values of the signal derived from speaking a word into a microphone or from scanning a character. The series of sample values are treated as a multidimensional vector signal having n compartments. The apparatus may be designed to learn and recognize a family of vectors by suitable progressive adjustment of the stored vector G. A particular input vector is termed F and the components are Fi. The classifying signal referred to above is the sealer product of the two vectors F and G. This is the sum of each component of the vector F multiplied by the corresponding component of the stored vector G. In the learning operation the vector F to be learned is applied together with an assigned sealer value B. The learning process is iterative, i.e. the stored vector G gradually assumes a value which will cause the proper output V to appear when the vector F is applied, V being equal to B, the assigned sealer value. During learning error values are produced which are the differences between the output produced and the assigned output value. From the error signal correction signals are obtained to be added to the stored values to produce a new stored vector value. This process, which is repeated for all the input vectors to be learned is the equivalent of solving a set of simultaneous linear equations by iteration. In the diagrammatic form of Fig. 3 the stored values are signals G 1 (x) &c. in conditioned memory 302. Sequence control 306 controls switches 303, 304, 311 and 318. Switch 304 passes the correction signals from generator 305 to the memory to modify the stored signals. Switch 303 connects the stored signals to function operator 308 where they are processed in turn with the incoming vector components F 1 (x) to be learned the products being summed to produce an output signal on line 320. The desired output signal is supplied from unit 310, selected in turn by switch 311 and applied on lead 313 to error detector 314 which subtracts the actual and desired outputs to produce the error signal to be applied to generator 305. This also receives the input vector component and produces the correction values to modify the stored signals. The transformation unit includes means to normalize for amplitude and for duration. For the latter the incoming waveforms are stored at one speed and re-read at a different speed to produce a signal of constant duration. In the recognition phase the output of the function operation 308, having a predetermined value indicative of the corresponding learned waveform, is applied to comparator 308. If the output signal is equal to any of the specified ranges a corresponding digitalized response is produced on output leads 319.